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Biomolecules
Special Issues
Systems Biology and Omics Approaches for Complex Human Disease
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Systems Biology and Omics Approaches for Complex Human Disease

A special issue of Biomolecules (ISSN 2218-273X). This special issue belongs to the section "Bioinformatics and Systems Biology".

Deadline for manuscript submissions: closed (28 February 2023) | Viewed by 17541

Special Issue Editors

Dr. Kumar Selvarajoo

E-Mail Website
Chief Guest Editor
1. Bioinformatics Institute, Agency for Science, Technology and Research, Biopolis, Singapore
2. Yong Loo Lin School of Medicine, National University of Singapore, Kent Rridge, Singapore
Interests: immune and cancer network modelling; self-organization; synthetic and systems biology; mathematical theories; data analytics; omics; non-linear dynamics
Prof. Dr. Alessandro Giuliani

E-Mail Website
Guest Editor
Environment and Health Department, Istituto Superiore di Sanità, 00161 Rome, Italy
Interests: data analysis; complex systems; systems biology; statistical mechanics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues, 

Living systems are highly complex and display self-organizing and emergent behaviors in their interactions with their environment. These behaviors often do not follow intuition or simple additive rules, ruling out any deterministic if-then chains. Systems biology, building up omics technologies, looks at developing a holistic view of biological systems, allowing to single out the organizing principles of biological regulation. This effort, thus, asks for an integration of different disciplines such as mathematics, computer science, physics, statistics, chemistry, and biology.

In this Special Issue, we host the latest cutting-edge and innovative research adopting integrative approaches that investigate complex human diseases from an interdisciplinary perspective.

We cordially invite scientists who feel uncomfortable with pure pattern recognition or gene list approaches and look for a renewed science integration to submit their original research (full articles or short reports), opinions, and review papers for publication in this Special Issue.

Dr. Kumar Selvarajoo
Prof. Dr. Alessandro Giuliani
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Biomolecules is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • theories for disease modeling
  • computational modeling of biological networks
  • data-analytics of genomics, transcriptomics, proteomics, and metabolomics
  • machine learning in complex diseases
  • evolutionary methods for disease origins
  • quantitative and integrative methods for disease analysis
  • software tools for disease interpretation

Published Papers (7 papers)

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Editorial

Jump to: Research, Review, Other

3 pages, 193 KiB  
Editorial
Systems Biology and Omics Approaches for Complex Human Diseases
by Kumar Selvarajoo and Alessandro Giuliani
Biomolecules 2023, 13(7), 1080; https://doi.org/10.3390/biom13071080 - 06 Jul 2023
Cited by 1 | Viewed by 1143
Abstract
For many years, there has been general interest in developing virtual cells or digital twin models [...] Full article
(This article belongs to the Special Issue Systems Biology and Omics Approaches for Complex Human Disease)

Research

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24 pages, 2824 KiB  
Article
An Efficient Bayesian Method for Estimating the Degree of the Skewness of X Chromosome Inactivation Based on the Mixture of General Pedigrees and Unrelated Females
by Yi-Fan Kong, Shi-Zhu Li, Kai-Wen Wang, Bin Zhu, Yu-Xin Yuan, Meng-Kai Li and Ji-Yuan Zhou
Biomolecules 2023, 13(3), 543; https://doi.org/10.3390/biom13030543 - 16 Mar 2023
Cited by 1 | Viewed by 1308
Abstract
Skewed X chromosome inactivation (XCI-S) has been reported to be associated with some X-linked diseases. Several methods have been proposed to estimate the degree of XCI-S (denoted as γ) for quantitative and qualitative traits based on unrelated females. However, there is no [...] Read more.
Skewed X chromosome inactivation (XCI-S) has been reported to be associated with some X-linked diseases. Several methods have been proposed to estimate the degree of XCI-S (denoted as γ) for quantitative and qualitative traits based on unrelated females. However, there is no method available for estimating γ based on general pedigrees. Therefore, in this paper, we propose a Bayesian method to obtain the point estimate and the credible interval of γ based on the mixture of general pedigrees and unrelated females (called mixed data for brevity), which is also suitable for only general pedigrees. We consider the truncated normal prior and the uniform prior for γ. Further, we apply the eigenvalue decomposition and Cholesky decomposition to our proposed methods to accelerate the computation speed. We conduct extensive simulation studies to compare the performances of our proposed methods and two existing Bayesian methods which are only applicable to unrelated females. The simulation results show that the incorporation of general pedigrees can improve the efficiency of the point estimation and the precision and the accuracy of the interval estimation of γ. Finally, we apply the proposed methods to the Minnesota Center for Twin and Family Research data for their practical use. Full article
(This article belongs to the Special Issue Systems Biology and Omics Approaches for Complex Human Disease)
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21 pages, 4849 KiB  
Article
Systems Biology Analysis of Temporal Dynamics That Govern Endothelial Response to Cyclic Stretch
by Michael W. Lai, Nathan Chow, Antonio Checco, Balvir Kunar, David Redmond, Shahin Rafii and Sina Y. Rabbany
Biomolecules 2022, 12(12), 1837; https://doi.org/10.3390/biom12121837 - 08 Dec 2022
Cited by 2 | Viewed by 1811
Abstract
Endothelial cells in vivo are subjected to a wide array of mechanical stimuli, such as cyclic stretch. Notably, a 10% stretch is associated with an atheroprotective endothelial phenotype, while a 20% stretch is associated with an atheroprone endothelial phenotype. Here, a systems biology-based [...] Read more.
Endothelial cells in vivo are subjected to a wide array of mechanical stimuli, such as cyclic stretch. Notably, a 10% stretch is associated with an atheroprotective endothelial phenotype, while a 20% stretch is associated with an atheroprone endothelial phenotype. Here, a systems biology-based approach is used to present a comprehensive overview of the functional responses and molecular regulatory networks that characterize the transition from an atheroprotective to an atheroprone phenotype in response to cyclic stretch. Using primary human umbilical vein endothelial cells (HUVECs), we determined the role of the equibiaxial cyclic stretch in vitro, with changes to the radius of the magnitudes of 10% and 20%, which are representative of physiological and pathological strain, respectively. Following the transcriptome analysis of next-generation sequencing data, we identified four key endothelial responses to pathological cyclic stretch: cell cycle regulation, inflammatory response, fatty acid metabolism, and mTOR signaling, driven by a regulatory network of eight transcription factors. Our study highlights the dynamic regulation of several key stretch-sensitive endothelial functions relevant to the induction of an atheroprone versus an atheroprotective phenotype and lays the foundation for further investigation into the mechanisms governing vascular pathology. This study has significant implications for the development of treatment modalities for vascular disease. Full article
(This article belongs to the Special Issue Systems Biology and Omics Approaches for Complex Human Disease)
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13 pages, 1467 KiB  
Article
Application of the Dynamical Network Biomarker Theory to Raman Spectra
by Takayuki Haruki, Shota Yonezawa, Keiichi Koizumi, Yasuhiko Yoshida, Tomonobu M. Watanabe, Hideaki Fujita, Yusuke Oshima, Makito Oku, Akinori Taketani, Moe Yamazaki, Taro Ichimura, Makoto Kadowaki, Isao Kitajima and Shigeru Saito
Biomolecules 2022, 12(12), 1730; https://doi.org/10.3390/biom12121730 - 22 Nov 2022
Cited by 4 | Viewed by 1955
Abstract
The dynamical network biomarker (DNB) theory detects the early warning signals of state transitions utilizing fluctuations in and correlations between variables in complex systems. Although the DNB theory has been applied to gene expression in several diseases, destructive testing by microarrays is a [...] Read more.
The dynamical network biomarker (DNB) theory detects the early warning signals of state transitions utilizing fluctuations in and correlations between variables in complex systems. Although the DNB theory has been applied to gene expression in several diseases, destructive testing by microarrays is a critical issue. Therefore, other biological information obtained by non-destructive testing is desirable; one such piece of information is Raman spectra measured by Raman spectroscopy. Raman spectroscopy is a powerful tool in life sciences and many other fields that enable the label-free non-invasive imaging of live cells and tissues along with detailed molecular fingerprints. Naïve and activated T cells have recently been successfully distinguished from each other using Raman spectroscopy without labeling. In the present study, we applied the DNB theory to Raman spectra of T cell activation as a model case. The dataset consisted of Raman spectra of the T cell activation process observed at 0 (naïve T cells), 2, 6, 12, 24 and 48 h (fully activated T cells). In the DNB analysis, the F-test and hierarchical clustering were used to detect the transition state and identify DNB Raman shifts. We successfully detected the transition state at 6 h and related DNB Raman shifts during the T cell activation process. The present results suggest novel applications of the DNB theory to Raman spectra ranging from fundamental research on cellular mechanisms to clinical examinations. Full article
(This article belongs to the Special Issue Systems Biology and Omics Approaches for Complex Human Disease)
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8 pages, 914 KiB  
Article
Integrating Text Mining into the Curation of Disease Maps
by Malte Voskamp, Liza Vinhoven, Frauke Stanke, Sylvia Hafkemeyer and Manuel Manfred Nietert
Biomolecules 2022, 12(9), 1278; https://doi.org/10.3390/biom12091278 - 10 Sep 2022
Cited by 1 | Viewed by 1625
Abstract
An adequate visualization form is required to gain an overview and ultimately understand the complex and diverse biological mechanisms of diseases. Recently, disease maps have been introduced for this purpose. A disease map is defined as a systems biological map or model that [...] Read more.
An adequate visualization form is required to gain an overview and ultimately understand the complex and diverse biological mechanisms of diseases. Recently, disease maps have been introduced for this purpose. A disease map is defined as a systems biological map or model that combines metabolic, signaling, and physiological pathways to create a comprehensive overview of known disease mechanisms. With the increase in publications describing biological interactions, efforts in creating and curating comprehensive disease maps is growing accordingly. Therefore, new computational approaches are needed to reduce the time that manual curation takes. Test mining algorithms can be used to analyse the natural language of scientific publications. These types of algorithms can take humanly readable text passages and convert them into a more ordered, machine-usable data structure. To support the creation of disease maps by text mining, we developed an interactive, user-friendly disease map viewer. The disease map viewer displays text mining results in a systems biology map, where the user can review them and either validate or reject identified interactions. Ultimately, the viewer brings together the time-saving advantages of text mining with the accuracy of manual data curation. Full article
(This article belongs to the Special Issue Systems Biology and Omics Approaches for Complex Human Disease)
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Review

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27 pages, 1269 KiB  
Review
Is Cancer Reversible? Rethinking Carcinogenesis Models—A New Epistemological Tool
by Andrea Pensotti, Marta Bertolaso and Mariano Bizzarri
Biomolecules 2023, 13(5), 733; https://doi.org/10.3390/biom13050733 - 24 Apr 2023
Cited by 2 | Viewed by 3539
Abstract
A growing number of studies shows that it is possible to induce a phenotypic transformation of cancer cells from malignant to benign. This process is currently known as “tumor reversion”. However, the concept of reversibility hardly fits the current cancer models, according to [...] Read more.
A growing number of studies shows that it is possible to induce a phenotypic transformation of cancer cells from malignant to benign. This process is currently known as “tumor reversion”. However, the concept of reversibility hardly fits the current cancer models, according to which gene mutations are considered the primary cause of cancer. Indeed, if gene mutations are causative carcinogenic factors, and if gene mutations are irreversible, how long should cancer be considered as an irreversible process? In fact, there is some evidence that intrinsic plasticity of cancerous cells may be therapeutically exploited to promote a phenotypic reprogramming, both in vitro and in vivo. Not only are studies on tumor reversion highlighting a new, exciting research approach, but they are also pushing science to look for new epistemological tools capable of better modeling cancer. Full article
(This article belongs to the Special Issue Systems Biology and Omics Approaches for Complex Human Disease)
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Other

15 pages, 589 KiB  
Opinion
Paradoxical Behavior of Oncogenes Undermines the Somatic Mutation Theory
by Noemi Monti, Roberto Verna, Aurora Piombarolo, Alessandro Querqui, Mariano Bizzarri and Valeria Fedeli
Biomolecules 2022, 12(5), 662; https://doi.org/10.3390/biom12050662 - 30 Apr 2022
Cited by 9 | Viewed by 4615
Abstract
The currently accepted theory on the influence of DNA mutations on carcinogenesis (the Somatic Mutation Theory, SMT) is facing an increasing number of controversial results that undermine the explanatory power of mutated genes considered as “causative” factors. Intriguing results have demonstrated that several [...] Read more.
The currently accepted theory on the influence of DNA mutations on carcinogenesis (the Somatic Mutation Theory, SMT) is facing an increasing number of controversial results that undermine the explanatory power of mutated genes considered as “causative” factors. Intriguing results have demonstrated that several critical genes may act differently, as oncogenes or tumor suppressors, while phenotypic reversion of cancerous cells/tissues can be achieved by modifying the microenvironment, the mutations they are carrying notwithstanding. Furthermore, a high burden of mutations has been identified in many non-cancerous tissues without any apparent pathological consequence. All things considered, a relevant body of unexplained inconsistencies calls for an in depth rewiring of our theoretical models. Ignoring these paradoxes is no longer sustainable. By avoiding these conundrums, the scientific community will deprive itself of the opportunity to achieve real progress in this important biomedical field. To remedy this situation, we need to embrace new theoretical perspectives, taking the cell–microenvironment interplay as the privileged pathogenetic level of observation, and by assuming new explanatory models based on truly different premises. New theoretical frameworks dawned in the last two decades principally focus on the complex interaction between cells and their microenvironment, which is thought to be the critical level from which carcinogenesis arises. Indeed, both molecular and biophysical components of the stroma can dramatically drive cell fate commitment and cell outcome in opposite directions, even in the presence of the same stimulus. Therefore, such a novel approach can help in solving apparently inextricable paradoxes that are increasingly observed in cancer biology. Full article
(This article belongs to the Special Issue Systems Biology and Omics Approaches for Complex Human Disease)
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